Probability and Statistical Inference (Statistics, a Series of Textbooks and Monographs)

Rating:
Summary: Solutions?
Review: Probability and Statistical Inference by Nitis Mukhopadhyay, Professor of Statistics, University of Connecticut, Storrs

Publisher and Date: Marcel Dekker, Inc., New York; March 2000

ISBN #: 0-8247-0379-0

Audience: Designed for two-semester or three-quarter courses allowing flexibility in the selection of topics beyond the core material! It is essentially a textbook for first-year graduate and upper-level undergraduate courses in probability and statistical inference. It can be used as a supplemental text for classes in Advanced Inference or Decision Theory. Students should have completed a calculus prerequisite.

Special Features: One will find novelty of treatment practically in every section and every topic. This gracefully organized textbook reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, numerous figures and tables, and computer simulations to develop and illustrate concepts. It employs over 1400 equations to reinforce its subject matter. The pre-publication reviewers called it a "ground breaking" text for first-year graduate and upper-level undergraduate courses in this subject.

Rating:
Summary: Author's Review
Review: Probability and Statistical Inference by Nitis Mukhopadhyay, Professor of Statistics, University of Connecticut, Storrs

Publisher and Date: Marcel Dekker, Inc., New York; March 2000

ISBN #: 0-8247-0379-0

Length of the book and price: Almost 700 pages long. A single textbook price

$95

It is an attractive feature. This textbook is significantly cheaper than any other comparable book at this level. The hard-copy book is available right now.

Audience: Designed for two-semester or three-quarter courses allowing flexibility in the selection of topics beyond the core material! It is essentially a textbook for first-year graduate and upper-level undergraduate courses in probability and statistical inference. It can be used as a supplemental text for classes in Advanced Inference or Decision Theory. Students should have completed a calculus prerequisite.

Special Features: One will find novelty of treatment practically in every section and every topic. This gracefully organized textbook reveals the rigorous theory of probability and statistical inference in the style of a tutorial, using worked examples, exercises, numerous figures and tables, and computer simulations to develop and illustrate concepts. It employs over 1400 equations to reinforce its subject matter. The pre-publication reviewers called it a "ground breaking" text for first-year graduate and upper-level undergraduate courses in this subject.

Worked examples: In many places, I let the Examples (worked out in detail) do the "talking," that is explaining concepts or techniques. The number of worked examples in this book is few folds more than those in several comparable books combined! Check it out.

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Rating:
Summary: The best textbook EVER!
Review: The textbook is the BEST in stat inference. You will find lots of examples, many tricks, and it's easy-reading!

Rating:
Summary: Solutions?
Review: This is actually a very nice text, and is easy reading, if you have atleast completed calc III.

The major draw back to this book is that it doesn't provide any solutions to end-of-chapter problems. As a result, you have no way of knowing if you have done the problem correctly. As a result, one needs to search through other texts to find similar problems to check there work. Based on this flaw, I would not recommend using this book as a reference, or as a required text for a graduate level Math Stat class.